Titre : Overview of Structural Reliability Analysis Methods — Part II: Sampling Methods 

Auteurs : Abdelkhalak El Hami, Bouchaïb Radi, ChangWu Huang,  

Revue : Uncertainties and Reliability of Multiphysical Systems 

Numéro : Optimization and Reliability 

Volume : 1 

Date : 2017/02/9 

DOI : 10.21494/ISTE.OP.2017.0116 

ISSN : 2514-569X 

Résumé : In Part II of the overview of structural reliability analysis methods, the category of sampling methods is reviewed. The basic Monte Carlo simulation is the foundation for sampling methods of reliability analysis. Sampling methods can evaluate the failure probability defined by both explicit and implicit performance function. With sufficient number of samples, simulation methods can give accurate results. However, for complex problem the computational cost is expensive. Thus, based on variance reduction techniques, some variants of basic Monte Carlo simulation method are proposed to reduce the computational cost. Monte Carlo simulation and its variants, including importance sampling, adaptive sampling, Latin hypercube sampling, directional simulation, and subset simulation, are presented and summarized in this paper. 

Éditeur : ISTE OpenScience